Query disambigution

ABSTRACT

A search query is resolved prior to being submitted to one or more search engines. The query is resolved such that the query unambiguously corresponds to a category included in a query ontology that relates search queries to query categories. The query may be resolved by supplementing the query with additional information corresponding to the category. For example, the query may be formatted into a canonical form of the query for the category. Alternatively or additionally, the query may be supplemented with one or more keywords that are associated with the category and that represent words or phrases that appear in a high percentage of search results for queries from the category. Resolving the query yields search results that more closely reflect search results desired by a user submitting the query.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.12/425,636, filed Apr. 17, 2009, which is a continuation of U.S.application Ser. No. 11/023,643, filed Dec. 29, 2004, which is nowissued as U.S. Pat. No. 7,562,069, which claims the benefit of andpriority to U.S. provisional application No. 60/584,137, filed Jul. 1,2004. Each of the aforementioned patent(s) and application(s) are herebyincorporated by reference in their entirety.

TECHNICAL FIELD

This document relates to retrieving and presenting search results forsearch queries.

BACKGROUND

Conventional search engines retrieve a set of search results thatcorrespond to a search query. Some search results may direct a user toInternet resources that do not interest the user, even though the searchresults match the search query. For example, this issue may arise when aquery relates to multiple different topics, one or more of which beingof little or no interest to the query submitter, in which case searchresults are produced that are representative of each of the differenttopics.

SUMMARY

In one general aspect, resolving an ambiguous query includes maintaininga query ontology that includes one or more query categories and one ormore queries associated with each of the one or more categories. The oneor more queries associated with a particular category included in thequery ontology represent queries associated with that particularcategory. A query is received from a user. The received query iscompared against one or more of the queries that are included within thequery ontology. Multiple categories that correspond to a query thatmatches the received query are identified from within the queryontology. One of the identified multiple categories is selected.Information associated with the selected category is identified fromwithin the query ontology. The received query is supplemented with theidentified information.

Implementations may include one or more of the following features. Forexample, the supplemented query may be submitted to a search engine, andsearch results for the supplemented query may be received from thesearch engine. Submitting the supplemented query to a search engine mayinclude identifying a search engine to handle the supplemented querybased on the selected category, and submitting the supplemented query tothe identified search engine. The supplemented query may be reformulatedto adhere to a syntax in which queries may be submitted to the searchengine.

Selecting one of the identified multiple categories may include enablingthe user to select among the identified multiple categories. Enabling auser to select among the identified multiple categories may includemaking canonical forms of the received query for the identified multiplecategories available for user selection as an identifier for one of themultiple categories.

Selecting one of the identified multiple categories may includeselecting, without user input, one of the identified multiple categoriesbased on characteristics of the received query. Selecting one of theidentified multiple categories based on characteristics of the receivedquery may include selecting one of the identified multiple categoriesbased on a category included in the query ontology that corresponds toonly a portion of the received query.

Selecting one of the identified multiple categories may includeselecting, without user input, one of the identified multiple categoriesbased on characteristics of the identified multiple categories.Selecting one of the identified multiple categories based oncharacteristics of the identified multiple categories may includeselecting one of the identified multiple categories that has beenselected most often.

Supplementing the received query with information associated with theselected category in the query ontology may include formatting thereceived query into a canonical form of the received query for theselected category, or supplementing the received query with one or morekeywords associated with the selected category in the query ontology.

Maintaining a query ontology may include arranging one or morecategories within the query ontology as nodes in a directed acyclicgraph. Identifying multiple categories included in the query ontologycorresponding to the received query may include identifying multiplecategories included in the query ontology that are ancestor or childcategories of categories included in the query ontology with which thereceived query is associated. Selecting one of the identified multiplecategories may include selecting a category included in the queryontology that is an ancestor or a child category of one of theidentified multiple categories. Supplementing the received query withinformation associated with the selected category in the query ontologymay include supplementing the received query with information associatedwith the selected ancestor or child category in the query ontology.

Supplementing the received query with the identified information mayinclude supplementing the received query with the identified informationwithout user perception of the supplemented query.

These general and specific aspects may be implemented using a system, amethod, or a computer program, or any combination of systems, methods,and computer programs.

Other features will be apparent from the description and drawings, andfrom the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an exemplary networked computingenvironment.

FIGS. 2A and 2B are block diagrams illustrating an exemplary ontologythat relates queries to query categories.

FIGS. 3A and 3B are block diagrams illustrating exemplary categoriesincluded in the ontology of FIGS. 2A and 2B.

FIG. 4 is a flow chart illustrating an exemplary process for retrievingsearch results for a query.

FIG. 5 is a flow chart illustrating an exemplary a process for resolvinga query that ambiguously corresponds to multiple categories of query.

FIG. 6 illustrates an exemplary interface for retrieving search resultsfor a query.

FIG. 7 illustrates another exemplary interface that relates to the FIG.6 interface but that is made perceivable after search results for aspecified query have been retrieved.

FIG. 8 illustrates another exemplary interface that relates to theinterfaces of FIGS. 6 and 7 but that is made perceivable after aspecified query has been resolved to correspond to a single querycategory.

FIG. 9 is a flow chart illustrating an exemplary process forsupplementing a query with keywords associated with a query categorycorresponding to the query.

FIG. 10 illustrates another exemplary interface that relates to the FIG.6 interface but that is made perceivable after search results for aquery that has been supplemented with keywords have been retrieved.

FIG. 11 is a flow chart illustrating an exemplary process foridentifying keywords for the query categories included in the ontologyof FIGS. 2A and 2B.

FIG. 12 is a flow chart illustrating an exemplary process for submittinga query to information sources corresponding to a query categoryassociated with the query.

FIG. 13A illustrates another exemplary interface for retrieving searchresults for a query.

FIG. 13B illustrates another exemplary interface that relates to theFIG. 13A interface but that is made perceivable after a query issubmitted to one or more expert domains corresponding to a category ofthe query.

FIG. 14 is a flow chart illustrating an exemplary process foridentifying expert domains for the query categories included in theontology of FIGS. 2A and 2B.

FIG. 15 is a flow chart illustrating an exemplary process for assigningscores to search results based on visual characteristics of surrogaterepresentations of the search results.

FIG. 16 illustrates exemplary surrogate representations of searchresults.

FIG. 17 is a flow chart illustrating an exemplary process for filteringsearch results based on scores assigned to the search results.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

A search query is resolved prior to being submitted to one or moresearch engines. The query is resolved such that the query unambiguouslycorresponds to a category included in a query ontology that relatessearch queries to query categories. The query may be resolved bysupplementing the query with additional information corresponding to thecategory. For example, the query may be formatted into a canonical formof the query for the category. Alternatively or additionally, the querymay be supplemented with one or more keywords that are associated withthe category and that represent words or phrases that appear in a highpercentage of search results for queries from the category. Resolvingthe query yields search results that more closely reflect search resultsdesired by a user submitting the query.

Referring to FIG. 1, an exemplary networked computing environment 100enables a user to search for particular Internet resources. Clientsystems 105 are manipulated by users to provide a query to a searchinterface 110 through with a search for particular Internet resources isperformed. The search interface 110 submits the query to one or moresearch engines 115 a-115 n. An ontology 125 and an ontology engine 120are used to disambiguate and reformulate the query before submission tothe search engines 115 a-115 n based on a category of the query. Asource selection module 130 identifies one or more of the search engines115 a-115 n to which the query should be submitted based on a categoryof the query. A network 135 interconnects the client system 105, thesearch interface 110, the search engines 115 a-115 n, the ontology 125,the ontology engine 120, and the source selection module 130.

The client system 105 includes one or more communications programs thatmay be used by the user to submit search queries for the particularInternet resources to the search interface 110. The communicationsprograms may include a web browser, an e-mail program, an instantmessaging program, a file transfer protocol (FTP) program, or anothercommunications program. The client system 105 also may include one ormore input devices, such as a keyboard, a mouse, a stylus, a camera, ora microphone, with which the user may specify the search queries. Theclient system 105 also includes one or more output devices, such as amonitor, a touch screen, speakers, or a printer, with which searchresults for the search queries from the search interface 110 may bepresented to the user. The search results may be indications of Internetresources that match the search queries, or the matching Internetresources themselves. The client system 105 also may be configured tocommunicate with other components of the networked computing environment100.

The search interface 110 receives queries specified by the user from theclient system 105. The search interface 110 may modify the queries andmay submit the queries to particular ones of the search engines 115a-115 n in order to retrieve search results for the received queriesthat represent search results desired by the user. For example, thesearch interface 110 may identify a query category among multiple querycategories that corresponds to a received query as a query category thatthe user intended for the received query. The query may be disambiguatedsuch that the query corresponds only to the intended category. Inaddition, the query may be reformulated with one or more keywordstypically found in search results for queries of the intended category.Furthermore, the search interface 110 may submit the received query onlyto particular ones of the search engines 115 a-115 n that typicallyreturn search results for queries of the intended category. Modifyingthe received query and submitting the received query only to particularones of the search engines 115 a-115 n based on the intended category ofthe query cause search results that are retrieved for the received queryto be representative of the intended category.

The search interface 110 also may assign or associate scores to thesearch results retrieved for the received query. The assigned scores maybe based on visual characteristics of surrogate representations of thesearch results that are received from the search engines 115 a-115 n.The search interface 110 also may sort or filter the search resultsbased on the assigned scores such that search results that are most orleast relevant to the received query made known to the client system 105and/or such that the most or least relevant are filtered out or throughfor presentation to the user.

The search engines 115 a-115 n identify Internet resources that match aquery that has been received from the search interface 110. The searchengines 115 a-115 n may identify the matching Internet resources usingone or more databases that include indexes of Internet resources. Theindexes may include keywords or descriptions of Internet resources thatare matched against the received query. If the keywords or descriptionfor an Internet resource matches the search query, then the Internetresource is identified as a search result for the received query. Thesearch engines 115 a-115 n may be configured to match the received queryagainst all possible Internet resources indexed in the databases, oragainst the Internet resources indexed in the databases that are from aparticular source. Furthermore, the search engines 115 a-115 n may bespecialized such that the databases for one of the search engines 115a-115 n index only particular Internet resources. For example, thesearch engine 115 a may be a search engine that is specialized for carssuch that the search engine 115 a indexes only Internet resources thatare related to cars.

The ontology 125, which also may be called a query ontology, relatessearch queries to categories of search queries. The ontology 125 maycategorize a very large number of search queries into a relatively smallnumber of categories of search queries. The ontology 125 also mayidentify one or more keywords for each of the categories of searchqueries. The keywords for a category may represent words or phrases thatappear in a high percentage of search results for queries correspondingto the category. In some implementations, the ontology 125 may identifyone or more expert domains for each of the categories of search queries,which represent domains from which a high percentage of search resultsfor queries corresponding to each particular category are identified.The structure of the ontology 125 will be described in further detailwith respect to FIGS. 2A, 2B, 3A, and 3B.

The ontology engine 120 is an interface to the ontology 125 that isaccessed by the search interface 110. The ontology engine 120 receives aquery from the search interface 110 and identifies one or morecategories from the ontology 125 that correspond to the received query.More particularly, the ontology engine 120 searches for the query in theontology 125 and returns the one or more categories from the ontology125 in which the query is found. In addition, the ontology engine 120may return keywords associated with the one or more categoriescorresponding to the query, as indicated by the ontology 125.

The source selection module 130 identifies one or more expert domainsthat may be used to identify appropriate search results for searchqueries. More particularly, the source selection module 130 receives aquery from the search interface 110 and identifies one or more expertdomains that may be used to identify appropriate search results for thereceived query. Such an identification may be made by first identifyingone or more categories for the received query using the ontology 125 andthe ontology engine 120, and then identifying one or more expert domainscorresponding to the identified categories. As a result, the sourceselection module 130 may relate query categories to expert domains thatare appropriate for the query categories. In implementations where theontology 125 identifies expert domains for the categories included inthe ontology 125, the source selection module 130 may be included in theontology engine 120. In such implementations, the source selectionmodule 130 may identify expert domains for queries based on informationincluded in the ontology 125.

The network 135 may be a network that connects the components of thenetworked computing environment 100, such as the Internet, the WorldWide Web, wide area networks, (WANs), local area networks (LANs), analogor digital wired and wireless telephone networks (e.g. a public switchedtelephone network (PSTN), an integrated services digital network (ISDN),or a digital subscriber line (xDSL)), radio, television, cable,satellite, and/or any other delivery mechanism for carrying data. Thecomponents of the networked computing environment 100 are connected tothe network 135 through communications pathways that enablecommunications through the network 135. Each of the communicationpathways may include, for example, a wired, wireless, cable or satellitecommunication pathway, such as a modem connected to a telephone line ora direct internetwork connection. The components of the networkedcomputing system 100 may use serial line internet protocol (SLIP),point-to-point protocol (PPP), or transmission control protocol/internetprotocol (TCP/IP) to communicate with one another over the network 135through the communications pathways.

Each of the components of the networked computing environment 100 may beimplemented using, for example, a general-purpose computer capable ofresponding to and executing instructions in a defined manner, a personalcomputer, a special-purpose computer, a workstation, a server, a device,a component, or other equipment or some combination thereof capable ofresponding to and executing instructions. The components may receiveinstructions from, for example, a software application, a program, apiece of code, a device, a computer, a computer system, or a combinationthereof, which independently or collectively direct operations, asdescribed herein. The instructions may be embodied permanently ortemporarily in any type of machine, component, equipment, storagemedium, or propagated signal that is capable of being delivered to thecomponents.

Further, each of the components of the networked computing environment100 includes a communications interface used send communications throughnetwork 110. The communications may include, for example, e-mailmessages, instant messages, audio data, video data, general binary data,or text data (e.g., encoded in American Standard Code for InformationInterchange (ASCII) format).

Referring to FIGS. 2A and 2B, a portion of one implementation of theontology 125 of FIG. 1 includes categories 205 a-205 z that are arrangedas nodes in a directed acyclic graph. Each of the categories 205 a-205 zis associated with one or more queries that are representative of thecategory. The queries that are associated with one of the categories 205a-205 z may be referred to as included in the category. Each of thecategories 205 a-205 z also may be associated with one or more keywordsand one or more expert domains for the category. As described above, thekeywords represent words or phrases that appear in a high percentage ofsearch results for queries associated with the category, and the expertdomains represent domains from which a high percentage of search resultsfor queries corresponding to the category are identified.

When a first category appears above a second category in the ontology125, the first category may be referred to as a parent category of thesecond category, and the second category may be referred to as a childcategory of the first category. For example, in relative terms, thescience category 205 d is a parent category, and the categories 205g-205 k are children categories of the science category 205 d. Ingeneral, an arrow directly from a first category to a second categoryindicates that the first category is a parent category of the secondcategory. More generally, one or more arrows from a first category to asecond category through one or more intermediate categories indicatethat the first category is an ancestor category of the second category,and that the second category is a child category of the first category.

A parent category includes queries that are more general than queriesincluded in a child category of the parent category. For example, thescience category 205 d is more general than the children categories 205g-205 k, which include the physics category 205 g, the chemistrycategory 205 h, the animals category 205 i, the astronomy category 205j, and the biology category 205 k. Queries associated with a particularcategory may be referred to as corresponding to the particular category,as well as to other categories included in the ontology 125 that areancestor or child categories of the particular category. Furthermore,categories that are ancestor or child categories of a category thatincludes a particular query may be referred to as corresponding to theparticular query. In the implementation of the ontology 125 illustratedin FIGS. 2A and 2B, each of the categories 205 a-205 z has only oneparent category. However, in other implementations of the ontology 125,each of the categories 205 a-205 z may have any number parent categoriesand any number of child categories.

In some implementations, some of the categories 205 a-205 z are notassociated with keywords or expert domains. In such implementations,keywords and expert domains for those categories may be keywords andexpert domains associated with one or more ancestor or child categoriesof those categories. For example, if no keywords and expert domains areassociated with the reptile category 205 q, keywords and expert domainsfrom the animals category 205 i, the science category 205 d, or the rootcategory 205 a may be used for the reptile category 205 q. When keywordsand expert domains are associated with a child category of ancestorcategory, keywords and expert domains from the ancestor category may beused in place of, or in addition to, the keywords and the expert domainsfor the child category.

In other implementations of the ontology 125, the categories 205 a-205 zare not arranged as nodes in a directed acyclic graph such thatrelationships do not exist between the categories 205 a-205 z. As aresult, keywords and expert domains for a query may be identified onlyfrom a category with which the query is associated. In suchimplementations, keywords, and expert domains may associated with all ofthe categories 205 a-205 z.

FIGS. 3A and 3B illustrate exemplary categories 205 m and 205 y from theontology 125. The birds category 205 m is a child category of theanimals category 205 i, the science category 205 d, and the rootcategory 205 a. The football teams category 205 y is a child category ofthe football category 205 t, the sports category 205 e, and the rootcategory 205 a. The categories 205 m and 205 y include names 305 a and305 b and associated query lists 310 a and 310 b, respectively. In thisexample, the category 205 m is named “Birds” and is associated withqueries that include “eagle,” “robin,” “cardinal,” and “blue jay,” andthe category 205 y is named “Football Teams” and is associated withqueries that include “Washington Redskins,” “Baltimore Ravens,” and“Philadelphia Eagles.” The queries listed in the query lists 310 a and310 b may be associated with the categories 205 m and 205 y manually orthrough automatic processes that identify appropriate categories forqueries.

The categories 205 m and 205 y may be associated with keyword lists 315a and 315 b. The keywords included in the keyword list 315 a representwords or phrases that appear in a high percentage of search results forthe queries included in the query list 310 a. Similarly, the keywordsincluded in the keyword list 315 b represent words that frequentlyappear in search results for the queries included in the query list 310b. In this example, the keyword list 310 a includes the keywords “bird,”“nest,” “egg,” “beak,” and “talon,” and the keyword list 310 b includesthe keywords “football,” “game,” “coach,” “quarterback,” and “receiver.”The keywords included in the keyword lists 315 a and 315 b may beidentified through execution of a process that will be described withrespect to FIG. 11.

The categories 205 m and 205 y also may be associated with expert domainlists 320 a and 320 b. The expert domains included in the expert domainlist 320 a represent domains from which a high percentage of searchresults for the queries included in the query list 310 a are retrieved.Similarly, the expert domains included in the expert domain list 320 brepresent domains from which a high percentage of search results for thequeries included in the query list 310 b are retrieved. In this example,the expert domain list 320 a includes the domains “www.hbw.com,”“birdingonthe.net,” “home.planet.nl,” “www.mangoverde.com,”“www.camacdonald.com,” “www.birdforum.net,” “www.bird-stamps.org,”“www.phthiraptera.org,” “www.scricciolo.com,” and “www.birdlife.net,”and the domain list 320 b includes the domains “www.nfl.com” and“www.football.com.” The expert domains included in the expert domainlists 320 a and 320 b may be identified through execution of a processthat will be described with respect to FIG. 14.

Both of the query lists 315 a and 315 b include a query that includesthe word “eagle.” As a result, when a query that includes the word“eagle” is received, for example, from the client system 105 of FIG. 1,both the category 205 m and the category 205 y will be identified ascorresponding to the received query. Such an identification may be madebecause “eagles” matches the query “eagle” from the query list 310 a andthe query “Philadelphia Eagles” from the query list 310 b. In otherwords, the query may ambiguously correspond to both of the categories205 m and 205 y, even though a user from which the query was receivedmay have intended only one of the queries 205 m and 205 y for the query.The query may be disambiguated in order to provide the user with searchresults that are appropriate for the category that the user intended forthe query.

Referring to FIG. 4, a process 400 is used to obtain search results fora query. The query is processed based on a category of the query. Theprocessed query is submitted to search engines that correspond to thecategory of the query. Search results received from the search enginesare scored and filtered based on the assigned scores. The process isexecuted by a search interface, such as the search interface 110 of FIG.1.

The process 400 begins when the search interface receives a query from auser (405). The search interface is accessed by a user of a clientsystem, such as the client system 105 of FIG. 1. The search interfaceprovides a user interface with which the user may specify the query tothe client system, and the client system makes the user interfaceperceivable to the user such that the user may specify the query. Oncespecified, the query is sent from the client system to the searchinterface, and the search interface receives the query.

The search interface resolves the received query when the received queryambiguously corresponds to multiple query categories (410). The querycategories are indicated by a query ontology, such as the query ontology125 of FIGS. 1, 2A, and 2B, which relates a query to one or more of thecategories. In general, the query is resolved to correspond to a subsetof the multiple query categories. For example, in typicalimplementations, the query is resolved to correspond only to one of themultiple query categories that corresponds to a query category that theuser intended for the query. Resolving the query is described in furtherdetail with respect to the exemplary process 410 of FIG. 5.

The search interface then supplements the resolved query with keywordsassociated with the single query category corresponding to the resolvedquery (415). The keywords may be associated with the single category inthe query ontology. The keywords represent words or phrases that arefound in a high percentage of search results for queries associated withthe single category in the query ontology. The keywords are identifiedand associated with the single category with a process such as thatdescribed below with respect to FIG. 11. The keywords are added to theresolved query such that search results retrieved for the query arerepresentative of the single category. An example of supplementing thequery with the keywords is described in further detail with respect toprocess 415 of FIG. 9.

The search interface routes the supplemented query to one or more searchengines corresponding to the supplemented query (420). Moreparticularly, the supplemented query is submitted to one or more searchengines that correspond to the single category in the query ontologycorresponding to the supplemented query. The search engines to which thesupplemented query is submitted represent search engines from which ahigh percentage of search results for queries associated with the singlecategory are retrieved. The search engines are identified and associatedwith the single category using, for example, a process described belowwith respect to FIG. 14. The supplemented query is submitted to the oneor more search engines such that search results retrieved in response tothe query are representative of the single category. An example ofsubmitting the supplemented query to the one or more search engines isdescribed in further detail with respect to process 420 of FIG. 12.

Search results for the received query are received from each of the oneor more search engines, and the search interface assigns scores to thereceived search results (425). Each of the one or more search enginesprovides surrogate representations of the search results to the searchinterface. A surrogate representation of a search result is a relativelyshort summary or excerpt of the search result that may be presented inplace of the search results itself. The search interface then assignsscores to the search results based on visual characteristics of thesurrogate representations of the search results. An example of assigningscores to the received search results is described in further detailwith respect to process 425 of FIG. 15.

The search interface filters the search results based on the assignedscores (430). More particularly, differences between scores assigned tothe search results are used to identify search results that should befiltered. In general, large differences in scores indicate that searchresults should be eliminated. The search results that are not eliminatedrepresent high quality search results for the query originally receivedfrom the user, though they may themselves be sorted based upon thescores. Filtering the search results based on the assigned scores isdescribed in further detail with respect to exemplary process 430 ofFIG. 17.

The search interface makes the filtered search results perceivable tothe user of the client system (435). More particularly, the searchinterface sends the surrogate representations of the search results thathave not been eliminated to the client system, and the client systempresents the surrogate representations to the user.

Particular implementations of the process 400 may include only a subsetof the operations 410-430. For example, in one implementation, thesearch results may not be filtered prior to being presented to the user.In another implementation, the query may not be supplemented withkeywords prior to being submitted to the one or more search engines. Inanother implementation, the query may be submitted to all availablesearch engines, instead of only to the search engines associated withthe category of the query. In yet another implementation, the query maynot be resolved, particularly when the query originally corresponds toonly one category in the query ontology.

Referring to FIG. 5, a process 410 represents one implementation of theoperation 410 of FIG. 4, in which a query that corresponds to multiplequery categories is resolved to correspond to a single category. Theprocess 410 may be executed by a search interface, such as the searchinterface 110 of FIG. 1, as part of the process 400 of FIG. 4.

The search interface identifies one or more categories corresponding toa received query in an ontology (505). The ontology may be the ontology120 of FIG. 1. The search interface may identify the one or morecategories using an ontology engine, such as the ontology engine 125 ofFIG. 1. More particularly, the search interface provides the receivedquery to the ontology engine, and the ontology engine searches for thereceived query in the ontology. The ontology engine does so by matchingthe received query against the queries associated with the categoriesincluded in the ontology. If a particular category corresponds to aquery that matches the received query, then the particular categorycorresponds to the received query. The ontology engine may identify allcategories included in the ontology that correspond to the receivedquery.

The search interface determines whether the received query correspondsto multiple categories (510). In other words, the search interface 510determines whether an indication of multiple categories from theontology that correspond to the received query is received from theontology engine.

If so, the received query is resolved such that the received querycorresponds to only one of the multiple categories (515). Moreparticularly, the search interface selects one of the multipleidentified categories (515). In one implementation, selecting themultiple identified categories includes enabling a user that specifiedthe received query to select one of the multiple categories. Forexample, indications of the multiple categories may be presented to theuser on a user interface with which the query was specified. The usermay select one of the indications, and the search interface selects thecorresponding category as the category to which the query should beresolved.

In another implementation, the search interface may use characteristicsof the received query to select one of the multiple identifiedcategories. For example, the search interface may identify one or morecategories from the ontology that correspond to a portion of thereceived query. The categories corresponding to the portion of thereceived query may be identified in a manner similar to how thecategories corresponding to the entire received query were identified.The portion of the received query may correspond to a single category,and the single category may be one of the multiple categories. In such acase, the single category is selected as the category to which thereceived query should be resolved. For example, the query “eaglesreceiver” may correspond to a football category and an animals category,while the “receiver” portion of the query may correspond to a footballcategory and an electronics category. The football category may beselected as the category to which the query should be resolved becauseboth the full query and the portion of the query correspond to thefootball category.

In another implementation, the search interface may use characteristicsof the multiple identified categories to select one of the multipleidentified categories. For example, an indication of a number of timeseach of the multiple identified categories has been selected may bemaintained, and the one of the multiple categories that has beenselected most often may be selected. Other indications of the popularityor appropriateness of the multiple identified categories may be used toselect one of the multiple identified categories for the received query.In some implementations, a combination of enabling the user to selectone of the multiple categories, identifying categories corresponding toa portion of the query, and identifying characteristics of multiplecategories corresponding to the received query may be used to select acategory for the received query.

The search interface supplements the query with information associatedwith or identifying the selected category (520). Supplementing the querywith information associated with or identifying the selected categorymay include formatting the query into a canonical form of the receivedquery for the selected category. The canonical form of the entered queryfor the selected category is a query associated with the selectedcategory that matches the entered query. When the query does not exactlymatch a query associated with the selected category, then the canonicalform of the query differs from the query. For example, the query“eagles” matches the query “Philadelphia Eagles,” which is associatedwith the football category. Consequently, “Philadelphia Eagles” may bethe canonical form of the query “eagles” for the football category.

Alternatively or additionally, the query may be supplemented with one ormore keywords associated with the selected category. The keywordsrepresent words or phrases found in a high percentage of search resultsfor queries associated with the selected category. The keywords may beassociated with the selected category in the ontology. The query may besupplemented with the keywords such that search results retrieved forthe supplemented query include at least one of the keywords.

Supplementing the received query may include reformulating the receivedquery to adhere to a syntax in which queries may be submitted to asearch engine to which the supplemented query will be submittedeventually. Each search engine to which the supplemented query may besubmitted accepts queries in a particular format, and the query may bereformulated to reflect the particular format of the search engine towhich the supplemented query will be submitted. The received query maybe supplemented such that the user does not authorize supplementing thequery with the associated information, or such that the user does notperceive the supplemented query.

Supplementing the query with the information causes the query tocorrespond to only the selected category. In other words, supplementingthe query resolves the query to the selected category. As a result, thesearch engine returns the resolved query (525). The returned query maybe processed further, or the returned query may be submitted to one ormore search engines to retrieve search results for the returned query.If the received query does not correspond to multiple categories in theontology (510), the received query, by default, corresponds to a singlecategory. As a result, the received query does not need to be resolvedand simply may be returned (525).

In some implementations, the categories included in the ontology arearranged as nodes in a directed acyclic graph, as illustrated in FIGS.2A and 2B. In such implementations, identifying categories thatcorrespond to the received category (505) may include identifyingancestor or child categories of categories included in the ontology withwhich the received query is associated. In addition, selecting one ofthe identified categories (515) may include selecting an ancestor or achild category of one of the identified categories. As a result,supplementing the received query with information associated with theselected category (520) may include supplementing the received querywith information associated with the selected ancestor or childcategory.

Referring to FIG. 6, a search tool user interface 600 may be presentedto a user of the client system 105 of FIG. 1 by the search interface 110of FIG. 1 when accessed. For example, the search tool user interface 600may be a web page sent to the client system 105 by the search interface110 in response to a request from the client system 105. The clientsystem 105 may present the search tool user interface 600 to the userwith a web browser running on the client system 105. The search tooluser interface includes a text field 605 and a button 610. The user mayenter a search query into the search field 605. As illustrated, the userhas entered “eagles” in the text field 605 as the search query.Selecting the button 610 after a search query has been entered into thetext field 605 submits the search query to the search interface 110 suchthat search results for the search query may be identified.

Referring to FIG. 7, the search tool interface 600 displays searchresults 705 a-705 e that have been retrieved for the search queryentered in the text field 605 after the submit button 610 has beenselected. In addition, category identifiers 710 a-710 c identifycategories in the ontology 125 of FIGS. 1, 2A and 2B corresponding tothe search query.

The category identifiers 710 a-710 c indicate that the search querycorresponds to multiple categories in the ontology 125. For example, oneof the queries corresponding to a musicians category in the ontology 125matches the search query, as indicated by the category identifier 710 a.In addition, the category identifier 710 b indicates that a querycorresponding to a football category in the ontology 125 matches thesearch query, and the category identifier 710 b indicates that a querycorresponding to a bird category in the ontology 125 matches the searchquery.

The category identifiers 710 a-710 c also may indicate canonical formsof the query entered in the text field 605 for the correspondingcategory. The canonical form of the entered query for a particularcategory is a query associated with the particular category that matchesthe entered query. For example, the entered query matches the query “TheEagles” that is associated with the musicians category, so “The Eagles”is the canonical form of the entered query for the musicians category.Similarly, “Philadelphia Eagles” is the canonical form of the enteredquery for the football category, and “eagles” is the canonical form ofthe entered query for the bird category.

The search results 705 a-705 e represent search results that wereretrieved for the search query before the search query wasdisambiguated. In other words, the search results 705 a-705 e wereretrieved for the search query before the search query was supplementedwith information associated with a category from the ontology 125 thatthe user intended for the search query. As a result, the search results705 a-705 e represent search results that are representative of themultiple categories. For example, the search results 705 a and 705 c arerepresentative of the musicians category, the search result 705 b isrepresentative of the football category, and the search results 705 dand 705 e are representative of the bird category.

One of the category identifiers 710 a-710 c may be selected by the userto indicate that the corresponding category was intended for the searchquery. For example, the user may select the category identifier 710 a toretrieve search results relating only to musicians that match the searchquery. The user may select the category identifier 710 b to retrievesearch results relating only to football that match the search query,and the user may select the category identifier 710 c to retrieve searchresults relating only to birds that match the search query. Moreover, auser interface may enable selection of more than one category, inresponse to which results corresponding to each selected category may beinterpreted seamlessly or visually distinguished through a visualindicator or screen position.

Referring to FIG. 8, the search tool user interface 600 displays searchresults 805 a-805 e, an original query indicator 810, a selectedcategory indicator 815, and an available category indicator 820 afterthe category identifier 710 a of FIG. 7 has been selected. When thecategory identifier 710 a was selected, the query entered in the textfield 605 was supplemented with information associated with the categoryassociated with the category identifier 710 a. For example, the querymay be reformatted into the canonical form of the query for the categoryselected with the category identifier 710 a. More particularly, themusicians category was selected with the category identifier 710 a, sothe query was reformatted into “The Eagles,” which is the canonical formof the query for the musicians category. In addition, the query may besupplemented with one or more keywords associated with the musicianscategory in the ontology 125. Such reformatting and supplementing may beindicated in the text field 605.

As a result of the disambiguation of the query by supplementing thequery with information associated with the musicians category, thesearch results 805 a-805 e are all representative of the musicianscategory. More particularly, the search results 805 a-805 e representInternet resources that match the supplemented query, which isrepresentative of only the musicians category in the query ontology 125.Therefore, the search results 805 a-805 e all relate to musicians named“The Eagles.”

The indicators 810-820 identify steps taken to retrieve the searchresults 805 a-805 e, which are representative of only one querycategory. More particularly, the indicators 8210-820 identify theoriginal query, the categories to which the original query corresponds,and the category to which the original query has been resolved. Theindicators 810-820 may allow navigation through the steps such that theoriginal query may be disambiguated in different manner, or such thatsearch results may be retrieved without first disambiguating theoriginal query.

The original query indicator 810 identifies the query that wasoriginally submitted before the query was disambiguated. For example,the query indicator 810 indicates that the original query was “eagles,”because that query was entered in the text field 605 of FIG. 6. In oneimplementation, the query listed in the original query indicator 810 maybe a link that may be selected to retrieve search results for theoriginal query without the original query being disambiguated. Forexample, selecting the query listed in the original query indicator maycause search results that are similar to the search results 705 a-705 eof FIG. 7 to be presented and displayed.

The selected category indicator 815 identifies a category to which thequery was resolved. More particularly, the selected category indicator815 identifies one of the multiple categories to which the originalquery corresponds whose corresponding category identifier was selected.For example, the selected category indicator 815 indicates that theoriginal query has been resolved to the musicians category as a resultof the category indicator 710 a of FIG. 7 being selected.

The available category indicator 820 identifies others of the multiplecategories to which the original query corresponds whose correspondingcategory identifiers were not selected. For example, the availablecategory indicator 820 indicates that the original query was notresolved to the football category or to the birds category because thecorresponding category indicators 710 b and 710 c of FIG. 7 were notselected. Each of the categories identified by the available categoryindicator 820 may be a link that may be selected to retrieve searchresults relating to that particular category. In other words, each ofthe categories listed in the available category indicator 820 may besimilar to one of the category identifiers 710 a-710 c of FIG. 7.

In other implementations of the search tool user interface 600 of FIGS.6-8, multiple sets of search results for the query may be presentedbefore one of the category identifiers 710 a-710 c has been selected.Each of the category identifiers 710 a-710 c may be associated with oneof the sets of the search results. The search results associated with acategory identifier represent one or more search results that arerepresentative of the query category corresponding to the categoryidentifier. One of the sets of search results may include search resultsthat were retrieved before the search query was disambiguated. Themultiple sets of search results may help the user to identify a categorythat was intended for the query. Selecting the category identifiercorresponding to the intended category may cause additional searchresults that are representative of the intended category to bepresented, as is illustrated in FIG. 8.

Referring to FIG. 9, a process 415 represents one implementation of theoperation 415 of FIG. 4, in which a query is supplemented with keywordsassociated with a category to which the query corresponds. The process415 may be executed by a search interface, such as the search interface110 of FIG. 1, as part of the process 400 of FIG. 4.

The search interface identifies a category corresponding to a receivedquery in an ontology (905). The category corresponding to the receivedquery may be identified in a manner similar to the process 410 of FIG.5. For example, the search interface may identify the category using anontology engine that interfaces with the ontology, such as the ontologyengine 120 of FIG. 1. If the received query corresponds to multiplecategories in the ontology, one of the categories may be selected(manually by the user or automatically without user control) for thereceived query, particularly when the received query has not beenresolved with the process 410 of FIG. 5 prior to execution of theprocess 415. In implementations where the categories included in theontology are arranged as nodes in a directed acyclic graph, identifyinga category that corresponds to the received query may includeidentifying an ancestor or a child category of a category included inthe ontology with which the received query is associated.

The search interface identifies one or more keywords associated with theidentified category (910). The keywords represent words or phrases foundin a high percentage of search results for queries associated with theselected category. In one implementation, the keywords are associatedwith the selected category in the ontology, as illustrated in FIGS. 3Aand 3B. In such an implementation, the search interface uses theontology engine to access the keywords from the ontology. In anotherimplementation, the keywords may be maintained in an external mappingthat relates query categories to keywords. Such a mapping may bemaintained by the search interface or the ontology engine. In such animplementation, identifying the keywords may include identifying thekeywords from the external mapping.

The search interface supplements the received query with the identifiedkeywords (915). The query may be supplemented with the keywords suchthat search results retrieved for the supplemented query include atleast one of the keywords. Supplementing the query with the keywordsincreases the chances that search results retrieved for the supplementedquery are representative of the identified category. A high percentageof search results for queries of the identified category include thekeywords, so search results that include one or more of the keywords arelikely to be representative of the identified category. In oneimplementation, prior to supplementing the query with the identifiedkeywords, the identified keywords may be presented to the user such thatthe user may select which of the identified keywords will be used tosupplement the received query. The supplemented query may bereformulated to adhere to a syntax in which queries may be submitted toa search engine to which the supplemented query will be submitted. Thereceived query may be supplemented such that the user does not authorizesupplementing the query with the keywords, or such that the user doesnot perceive the supplemented query.

Maintaining keywords for query categories may be more advantageous thanmaintaining keywords for individual queries, particularly when thenumber of categories is significantly smaller than the number ofindividual queries. Maintaining keywords for query categories instead offor individual queries reduces the storage space required for thekeywords.

Referring to FIG. 10, the search tool user interface 600 displays searchresults 1005 a-1005 e that were retrieved for a query entered in thetext field 605 after the query was supplemented with one or morekeywords associated with a category that was intended for the query. Thesearch tool user interface 600 illustrated in FIG. 10 may be presentedafter the button 610 of the search tool user interface 600 illustratedin FIG. 6 has been selected, if the search query entered into the textfield 605 of FIG. 6 corresponds to only one category. Alternatively, ifthe search query entered in the text field 605 corresponds to multiplecategories, then the search tool user interface 600 illustrated in FIG.10 may be presented after one (or more) of the category identifiers 710a-710 c of FIG. 7 has been selected.

The search results 1005 a-1005 e are representative of the bird categoryof the ontology 125 because the query entered in the text field 605 hasbeen supplemented with keywords associated with the bird category. Thekeywords may be added to the query as a result of the querycorresponding only to the bird category, or as a result of the selectionof the category identifier 710 c of FIG. 7, which corresponds to thebird category. In addition to including the original query “eagles,” thesearch results 1005 a-1005 e also may include one or more of thekeywords that were used to supplement the original query.

The keywords with which the query has been supplemented may or may notbe made perceivable to the user from which the query was received. As aresult, the query may or may not be modified within the text field 605,though the query has been modified within the text field in theillustrated search tool user interface 600.

Referring to FIG. 11, a process 1100 is used to associate keywords withquery categories included in a query ontology. The process 1100identifies words or phrases that appear in a high percentage of searchresults for queries from a particular category in the query ontology andassociates the identified words with the particular category as keywordsfor the particular category. The keywords are used to supplement queriesthat correspond to the particular category such that search resultsretrieved for the particular category are representative of theparticular category. The process 1100 is executed by the ontology engine120 to prepare the ontology 125, both of FIG. 1.

The process 1100 begins when an ontology that relates queries to querycategories is maintained and/or accessed (1105). For example, anontology that is similar to the ontology 125 of FIGS. 1, 2A, and 2B ismaintained.

The ontology engine submits queries associated with categories includedin the ontology to one or more search engines (1110). In oneimplementation, all queries included in the ontology are submitted tothe one or more search engines. In another implementation, a particularnumber of queries from each of the categories included in the ontologyare submitted to the one or more search engines. In general, any numberof queries included in the ontology may be submitted, particularly ifthe submitted queries evenly represent the categories included in theontology.

Furthermore, in some implementations, the queries may be submitted toall available search engines or to a subset of the available searchengines. For example, the queries may be submitted to a general searchengine from which many types of search results may be retrieved.Alternatively, the queries may be submitted to multiple search enginesfrom which specialized types of search results may be retrieved. Asanother example, the queries may be submitted both to general andspecialized search engines. In general, the queries may be submitted toany set of search engines, particularly if different types of searchresults may be retrieved evenly from the search engines. Search resultsfor the submitted queries are received from the one or more searchengines to which the queries were submitted (1115).

The ontology engine determines a frequency of occurrence in the receivedsearch results for each word that appears in the received search results(1120). The ontology engine also may determine a frequency of occurrencein the received search results for one or more phrases that appear inthe received search results. Determining the frequency of occurrence fora word or a phrase may include determining a probability that the wordor the phrase appears in one of the received search results. Such aprobability may be defined as the ratio of the number of the receivedsearch results that include the word or the phrase to the number of thereceived search results. Alternatively, determining the frequency ofoccurrence for a word or a phrase may include determining a number ofthe received search results that include the word or the phrase. In oneimplementation, the frequencies of occurrence for the words or thephrases appearing in the received search results may be determined usingonly a subset of the retrieved search results. For example, a particularnumber of the search results that most closely match each of thesubmitted queries may be used to determine the frequencies.

The determined frequencies of occurrence represent a base statisticalmodel of word or phrase frequency from a random or general collection ofsearch results. The determined frequencies will be compared tofrequencies determined for search results for queries from a particularcategory in the query ontology. Words or phrases with higher frequenciesin search results for queries from the particular category will beidentified as keywords for the particular category.

The ontology engine then selects a category from within the ontology(1125). The ontology engine submits queries associated with the selectedcategory to one or more search engines (1130). Some or all of thequeries associated with the selected category may be submitted to theone or more search engines. The queries may be submitted to the samesearch engines to which the queries from the categories were previouslysubmitted. Search results for the submitted queries from the selectedcategory are received from the one or more search engines (1135).

The ontology engine determines a frequency of occurrence in the searchresults received for the submitted queries from the selected categoryfor each word that appears in the received search results (1140). Theontology engine also may determine a frequency of occurrence in thereceived search results for one or more phrases that appear in thereceived search results. The frequencies may be determined in a mannersimilar to how the frequencies were previously determined using searchresults received for the queries included in the ontology.

For each word that appears in the received search results, the ontologyengine compares the frequency of occurrence in the search results forthe queries from the selected category to the frequency of occurrence inthe search results for the queries from the categories (1145). Theontology engine also may compare the frequencies of occurrence for thephrases that appear in the received search results. In general,comparing the two frequencies for a particular word or phrase indicateswhether the particular word or phrase appears more frequently in thesearch results for the queries from the selected category. Comparing thetwo frequencies also may indicate whether the particular word or phraseappears with relatively equal frequency in both the search results forthe queries from the selected category and the search result for thequeries from the categories. Comparing the two frequencies may includeidentifying a weighting factor for the word or the phrase. The weightingfactor indicates the relative difference between the two frequencies. Inone implementation, a high weighting factor may indicate that the wordor the phrase occurs more frequently in the search results for thequeries from the selected category than in the search results for thequeries from the categories. On the other hand, a low weighting factormay indicate that the word or the phrase does not occur more frequentlyin the search results for the queries from the selected category than inthe search results for the queries from the categories.

Words that appear more frequently in the search results for the queriesfrom the selected category of the query ontology are identified askeywords for the selected category (1150). In addition, one or morephrases that appear more frequently in the search results for thequeries from the selected category of the query ontology may beidentified as keywords for the selected category. The identification ofthe keywords may be based on the weighting factors of the words or thephrases that appear in the received search results. In oneimplementation, a particular number of words or phrases with the highestweighting factors are identified as the keywords. In anotherimplementation, words or phrases with weighting factors that exceed athreshold weighting factor are identified as the keywords.

A user may be enabled to add or remove keywords for the selectedcategory (1155). For example, the user may access the ontology enginewith a client system, such as the client system 105 of FIG. 1, to add orremove keywords for the selected category. Alternatively, the user mayaccess the ontology engine directly to specify the keywords. The userthat adds or removes keywords for the selected category may be an editoror an administrator of the ontology and the ontology engine. Enablingthe user to review the automatically identified keywords enables theuser to determine that the best keywords have been identified for theselected category. The user may remove keywords that are not the bestkeywords for the selected category. The user also may add keywords thathave not been automatically identified as the best keywords for theselected category. In some implementations, the user may be preventedfrom removing one or more of the keywords. For example, the user may beprevented from removing the keyword for which the best weighting factorhas been identified. As a result, the keyword with the best weightingfactors always may be associated with and used for the selectedcategory.

The ontology engine associates one or more of the identified keywordswith the selected category (1160). In one implementation, the keywordsare stored with the selected category in the query ontology, as isillustrated in FIGS. 2A and 2B. In another implementation, the keywordsare associated with the selected category in a mapping of categories tokeywords for the categories that is external to the query ontology. Sucha mapping may be maintained by the ontology engine.

The ontology engine determines whether keywords have been identified forall categories included in the query ontology, or whether keywords needto be identified for more categories (1165). If so, then the ontologyengine selects one of the categories for which keywords have not alreadybeen identified (1125), submits queries associated with the selectedcategory to one or more search engines (1130), and receives searchresults for the submitted query (1135). Frequencies of word or phraseoccurrence are determined (1140), and the frequencies are compared topreviously determined frequencies of occurrence of words or phrases thatappear in search results for the queries from the categories (1145).Based on the comparison, keywords for the selected category areidentified (1150), modified by a user (1155), and associated with theselected category (1160). In this manner, keywords are identifiedsequentially for each category included in the query ontology, untilkeywords have been identified for all categories included in the queryontology, at which point the process 1100 is done (1170).

Referring to FIG. 12, a process 420 represents one implementation of theoperation 420 of FIG. 4, in which a query is submitted to informationsources associated with a category to which the query corresponds. Theprocess 420 may be executed by a search interface, such as the searchinterface 110 of FIG. 1, as part of the process 400 of FIG. 4.

The search interface identifies possible combinations of terms from areceived query (1205). For example, if the received query includes threeterms, the possible combinations may include the first term, the secondterm, the third term, the first and second terms, the second and thirdterms, and the first, second, and third terms. In this and typicalimplementations, the possible combinations of terms from the receivedquery represent subsets of consecutive terms from the received query,and the order of the consecutive terms is maintained. Suchimplementations are advantageous because the order and location of theterms in the query typically affect the subject matter, and consequentlythe category, of the query. For example, for the query “wooden Venetianblind, the combination “Venetian blinds” may have more relevance to themeaning of the query than the combination “blind Venetian” or thecombination “wooden blind.” Furthermore, limiting the number ofallowable combinations of the query terms limits the number ofcategories that may correspond to the combinations, which may limit thenumber of information sources to which the search query is submitted.However, in other implementations, the possible combinations also mayinclude subsets of nonconsecutive terms from the received query (forexample, in the initial example of three terms, the first and thirdterms), and the terms in each of the possible combinations may bepermuted to identify additional combinations. Identifying the possiblecombinations of terms of the received query may be referred to asn-gramming the received query.

The search interface identifies one or more categories corresponding toeach of the possible combinations of the terms in an ontology (1210).The categories corresponding to each of the combinations may beidentified in a manner similar to the process 410 of FIG. 5. Forexample, the search interface may identify the one or more categoriesfor the combination using an ontology engine that interfaces with theontology, such as the ontology engine 120 of FIG. 1. In implementationswhere the categories included in the ontology are arranged as nodes in adirected acyclic graph, identifying the one or more categories thatcorrespond to the combination may include identifying ancestor or childcategories of categories included in the ontology with which thecombination is associated. The categories corresponding to each of thepossible combinations represent categories for the entire query.

The categories corresponding to the combinations of terms of the querymay be filtered based on a determination of whether the categories maycorrespond to a single query (1215). For example, an indication ofwhether a subset of the categories has corresponded to a previouslyreceived query may be used to determine whether the categories should befiltered. Alternatively or additionally, a probability that a subset ofthe categories corresponds to a single query may be used to determinewhether the categories should be filtered. The probability may be basedon categories identified for previously received queries. For example,the combinations of terms from the query may correspond to threecategories. The three categories together may not have corresponded to apreviously received query, but two of the categories may have a highprobability of both corresponding to a single query. As a result, thetwo categories may be identified as categories for the query, and thethird category may be eliminated. Reducing the number of categories thatcorrespond to the query may reduce the number of information sources towhich the categories are submitted.

The search interface identifies one or more information sourcesassociated with the identified categories that have not been eliminated(1220). The information sources represent domains from which a highpercentage of search results for queries corresponding to the identifiedcategories are identified. The information sources represent experts onthe identified categories and all corresponding queries and keywords ingeneral, rather than experts on any particular query associated with theidentified categories (although a particular expert may provideexpertise on both). In one implementation, the information sources areassociated with the identified categories in the ontology, asillustrated in FIGS. 3A and 3B. In such an implementation, the searchinterface uses the ontology engine to access the information sourcesfrom the ontology. In another implementation, the information sourcesmay be maintained in an external mapping that relates query categoriesto information sources for the queries. Such a mapping may be maintainedby a source selection module, such as the source selection module 130 ofFIG. 1. In such an implementation, identifying the information sourcesmay include identifying the information sources from the externalmapping.

The search interface submits the received query to the identifiedinformation sources (1225). Submitting the query to the identifiedinformation sources may include submitting the query to the identifiedinformation sources such that the information sources may identifysearch results for the query from the information sources. Submittingthe query to the identified information sources also may includesubmitting the query to one or more search engines with an instructionto return search results from only the identified information sources.Submitting the query to the identified information sources increases thechances that search results retrieved for the query are representativeof the category of the query. A high percentage of search results forqueries from the categories corresponding to the query are identifiedfrom the identified information sources, so search results from theidentified information sources are likely to be representative of thecategories corresponding to the query.

Identifying information sources that correspond to one of thecombinations of terms from the query as appropriate for the queryeliminates the need to relate all possible queries to query categories.The number of possible queries prohibits identifying a category for eachof the queries. Furthermore, the set of possible queries is constantlychanging. However, the number of terms that may be used to constructqueries allows for one or more categories to be identified for each ofthe terms, and the set of query terms is relatively fixed. Under theassumption that the categories of a query are the categories of terms ofthe query, such classification of query terms enables classification ofan otherwise prohibitively large number of queries.

Submitting queries to a subset of the available search engines, insteadof to all of the available search engines, may be advantageous becausemost of the available search engines may not provide desirable searchresults for each query. Furthermore, network resources are preservedbecause communication occurs only between a limited number of systems.In general, a smaller number of search engines to which a query issubmitted corresponds to a larger amount of network resources that arepreserved, so a small subset of search engines that return high qualitysearch results may be used to preserve a large amount of networkresources. In addition, identifying information sources for querycategories may be better than identifying information sources forindividual queries, or for individual query terms. This may beparticularly true when the number of categories is significantly smallerthan the number of individual queries. Maintaining indications ofinformation sources for query categories instead of for individualqueries or query terms reduces the storage space required for theindications of the information sources.

Referring to FIG. 13A, a search tool user interface 1300 is similar tothe search tool user interface 600 of FIGS. 6, 7, 8, and 10. The searchtool user interface 1300 includes a text field 1305 into which a usermay enter a search query, and a button 1310 that may be selected toretrieve search results 1315 a-1315 f for the entered query. Asillustrated, the user has entered “eagles” in the text field 1305, andthe button 1310 has been selected to retrieve the search results 1315a-1315 f. The search tool user interface 1300 also includes categoryidentifiers 1320 a-1320 c that identify query categories with which theentered query is associated.

The category identifiers 1320 a-1320 c indicate that the query enteredin the text field 1305 is associated with multiple categories in theontology 125. More particularly, the query is associated with amusicians category, as indicated by the category identifier 1320 a, abirds category, as indicated by the category identifier 1320 b, and afootball category, as indicated by the category identifier 1320 c. Thesearch results 1315 a-1315 f may represent search results that wereretrieved for the search query before the search query was disambiguatedto correspond only to one of the multiple categories, for example, withthe process 410 of FIG. 5. As a result, all of the search results 1315a-1315 f may not have been retrieved from information sourcescorresponding to a particular one of the multiple categories. Instead,the search results 705 a-705 e are from information sources thatcorrespond to more than one of the multiple categories, or that do notcorrespond to any of the multiple categories. As a result, the searchresults 1315 a-1315 e may be representative of the multiple categories.For example, the search result 1315 a and 1315 c are representative ofthe football category, the search results 1315 b and 1315 d arerepresentative of the musicians category, and the search results 1315 eand 1315 f are representative of the bird category.

One of the category identifiers 1320 a-1320 c may be selected by theuser to indicate that the corresponding category was intended for thesearch query. For example, the user may select the category identifier1320 a, 1320 b, or 1320 c to indicate that the musicians category, thebirds category, or the football category, respectively, was intended forthe query. The query then may be submitted to one or more informationsources corresponding to the intended category such that the searchresults 1305 a-1305 f are retrieved from the information sources.

Referring to FIG. 13B, the search tool user interface 1300 displaysinformation source indicators 1325 a-1325 j and search results 1330a-1330 f after the category identifier 1320 b of FIG. 13A has beenselected. The information source indicators 1325 a-1325 j identifyinformation sources corresponding to the birds category, which wasselected for the query through selection of the category identifier 1320b. For example, each of the information source indicators 1325 a-1325 bcorresponds to an expert domain listed in the expert domain list 320 aof FIG. 3A for the exemplary birds category 205 m from the exemplaryontology 125 of FIGS. 2A and 2B.

Each of the search results 1330 a-1330 f has been retrieved from one ofthe information sources for which an information source indicator 1325a-1325 j is displayed. Because the search results 1330 a-1330 f areretrieved from one or more of the information sources corresponding tothe birds category, the search results 1330 a-1330 f are allrepresentative of the birds category. Furthermore, selecting one of theinformation source indicators 1325 a-1325 j may cause search resultsonly from the corresponding information source to be retrieved anddisplayed to the exclusion or apparent visual preference or relativeorder with respect to results from other of the sources, which furtherensures that the search results are representative of the birds categoryin the above example.

After selection of the category identifier 1320 b, the categoryidentifiers 1320 a and 1320 c may be selected to retrieve search resultsfor the query from information sources corresponding to the musicianscategory and the football category, respectively. Selecting one of thecategory identifiers 1320 a and 1320 c may cause one or more informationsource indicators for information sources corresponding to the selectedcategory to be displayed. Each of the information source indicators maybe selected to cause search results only from the correspondinginformation source to be retrieved and displayed.

In other implementations of the search tool user interface 1300 of FIGS.13A and 13B, multiple sets of search results for the query may bepresented before one of the category identifiers 1320 a-1320 c has beenselected. Each of the category identifiers 1320 a-1320 c may beassociated with one of the sets of the search results. The searchresults associated with a category identifier represent one or moresearch results that have been retrieved from one or more informationsources corresponding to the query category corresponding to thecategory identifier. One of the sets of search results may includesearch results that were retrieved before the search query wasdisambiguated such that the search results may have been retrieved frommultiple domains that do not necessarily correspond to a particularquery category. The multiple sets of search results may help the user toidentify a category that was intended for the query. Selecting thecategory identifier corresponding to the intended category may retrieveadditional search results from one or more information sourcescorresponding to the query category for presentation, as is illustratedin FIG. 13B.

Referring to FIG. 14, a process 1400 is used to associate expert domainswith query categories included in a query ontology. The process 1400identifies domains from which a high percentage of search results forqueries from a particular category in the query ontology are identifiedand associates the identified domains with the particular category asexpert domains for the particular category. Queries that correspond tothe particular category are submitted to the expert domains such thatsearch results retrieved for the particular category are representativeof the particular category. In other words, the expert domains are theinformation sources to which a query that corresponds to the particularcategory are routed during the process 420 of FIG. 12. The process 1400is executed by the ontology engine 120 to prepare the ontology 125, bothof FIG. 1.

The process 1400 begins when an ontology that relates queries to querycategories is maintained and/or accessed (1405). For example, anontology that is similar to the ontology 125 of FIGS. 1, 2A, and 2B ismaintained.

The ontology engine submits queries associated with categories includedin the ontology to one or more search engines (1410). In oneimplementation, all queries included in the ontology are submitted tothe one or more search engines. In another implementation, a particularnumber of queries from each of the categories included in the ontologyare submitted to the one or more search engines. In general, any numberof queries included in the ontology may be submitted, particularly ifthe submitted queries evenly represent the categories included in theontology.

Furthermore, in some implementations, the queries may be submitted toall available search engines or to a subset of the available searchengines. For example, the queries may be submitted to a general searchengine from which many types of search results may be retrieved.Alternatively, the queries may be submitted to multiple search enginesfrom which specialized types of search results may be retrieved. Asanother example, the queries may be submitted both to general andspecialized search engines. In general, the queries may be submitted toany set of search engines, particularly if different types of searchresults may be retrieved evenly from the search engines. Search resultsare received from the search engines to which the queries were submitted(1415).

The ontology engine determines a frequency of occurrence in the receivedsearch results for each domain from which one of the received searchresults was retrieved (1420). Determining the frequency of occurrencefor a domain may include determining a probability that one of thereceived search results was retrieved from the domain. Such aprobability may be defined as the ratio of the number of the receivedsearch results that were retrieved from the domain to the number of thereceived search results. Alternatively, determining the frequency ofoccurrence for a domain may include determining a number of the receivedsearch results that were retrieved from the domain. In oneimplementation, the frequencies of occurrence for the domains from whichthe search results were retrieved may be determined using only a subsetof the retrieved search results. For example, a particular number of thesearch results that most closely match each of the submitted queries maybe used to determine the frequencies.

The determined frequencies of occurrence represent a base statisticalmodel of domain frequency from a random or general collection of searchresults. The determined frequencies will be compared to frequenciesdetermined for search results for queries from a particular category inthe query ontology. Domains with higher frequencies in search resultsfor queries from the particular category will be identified as expertdomains for the particular category.

The ontology engine then selects a category from within the ontology(1425). The ontology engine submits queries associated with the selectedcategory to one or more search engines (1430). Some or all of thequeries associated with the selected category may be submitted to theone or more search engines. The queries may be submitted to the samesearch engines to which the queries from the categories were previouslysubmitted. Search results for the submitted queries from the selectedcategory are received from the one or more search engines (1435).

The ontology engine determines a frequency of occurrence in the searchresults received for the queries from the selected category for eachdomain from which one of the received search results was retrieved(1440). The frequencies may be determined in a manner similar to how thefrequencies were previously determined using search results received forthe queries included in the ontology.

For each domain from which one of the received search results wasretrieved, the ontology engine compares the frequency of occurrence inthe search results for the queries from the selected category to thefrequency of occurrence in the search results for the queries from thecategories (1445). In general, comparing the two frequencies for aparticular domain indicates whether the particular domain occurs morefrequently in the search results for the queries from the selectedcategory. Comparing the two frequencies also may indicate whether theparticular domain occurs with relatively equal frequency in both thesearch results for the queries from the selected category and the searchresult for the queries from the categories. Comparing the twofrequencies may include identifying a weighting factor for the domain.The weighting factor indicates the relative difference between the twofrequencies. A high weighting factor may indicate that the domain occursmore frequently in the search results for the queries from the selectedcategory than in the search results for the queries from the categories.On the other hand, a low weighting factor may indicate that the domaindoes not occur more frequently in the search results for the queriesfrom the selected category than in the search results for the queriesfrom the categories.

Domains that appear more frequently in the search results for thequeries from selected category of the query ontology are identified asexpert domains for the selected category (1450). The identification ofthe expert domains may be based on the weighting factors of the domainsthat appear in the received search results. In one implementation, aparticular number of domains with the highest weighting factors areidentified as the expert domains. In another implementation, domainswith weighting factors that exceed a threshold weighting factor areidentified as the expert domains.

A user may be enabled to add or remove expert domains for the selectedcategory (1455). For example, the user may access the ontology enginewith a client system, such as the client system 105 of FIG. 1, to add orremove expert domains for the selected category. Alternatively, the usermay access the ontology engine directly to specify the expert domains.The user that adds or removes expert domains for the selected categorymay be an editor or an administrator of the ontology and the ontologyengine. Enabling the user to review the automatically identified expertdomains enables the user to determine that the best expert domains havebeen identified for the selected category. The user may remove expertdomains that are not the best expert domains for the selected category.The user also may add expert domains that have not been automaticallyidentified as the best expert domains for the selected category. In someimplementations, the user may be prevented from removing one or more ofthe expert domains. For example, the user may be prevented from removingthe expert domain for which the best weighting factor has beenidentified. As a result, the expert domains with the best weightingfactors always may be associated with and used for the selectedcategory.

The ontology engine associates one or more of the identified expertdomains with the selected category (1460). In one implementation, theexpert domains are stored with the selected category in the queryontology, as is illustrated in FIGS. 2A and 2B. In anotherimplementation, the expert domains are associated with the selectedcategory in a mapping of categories to expert domains for the categoriesthat is external to the query ontology. Such a mapping may be maintainedby the ontology engine.

The ontology engine determines whether expert domains have beenidentified for all categories included in the query ontology or whetherexpert domains need to be identified for more categories (1465). If so,then the ontology engine selects one of the categories for which expertdomains have not already been identified (1425), submits queriesassociated with the selected category to one or more search engines(1430), and receives search results for the submitted query are received(1435). Frequencies of domain occurrence are determined (1440), and thefrequencies are compared to previously determined frequencies ofoccurrence of domain that appear in search results for the queries fromthe categories (1445). Based on the comparison, expert domains for theselected category are identified (1450), modified by a user (1455), andassociated with the selected category (1460). In this manner, expertdomains are identified sequentially for each category included in thequery ontology, until expert domains have been identified for allcategories included in the query ontology, at which point the process1400 is done (1470).

Referring to FIG. 15, a process 425 represents one implementation of theoperation 425 of FIG. 4, in which scores are assigned to search resultsbased on visual characteristics of surrogate representations of thesearch results. Assigning scores based on the surrogate representationsmimics user assessment of the relevance of the search results. Theprocess 425 may be executed by a search interface, such as the searchinterface 110 of FIG. 1, as part of the process 400 of FIG. 4.

The search interface receives surrogate representations of searchresults for a query from one or more search engines (1505). Moreparticularly, the search interface receives a set of search results forthe query from each of the one or more search engines. The searchresults in a set of search results may be ordered based on scoresassigned by the search engine from which the set of search results wasreceived. The query may have been submitted to the one or more searchengines during the process 400 of FIG. 4, or during the process 420 ofFIG. 12.

The surrogate representations of the search results are relatively shortsummaries or excerpts of the search results that may be presented inplace of the search results themselves, thus enabling an overview ofvarious search results to be perceived by a user concurrently. Thesurrogate representation of a search result may include a title of thesearch result, a short description or summary of the search result, anaddress from which the search result may be accessed, a hyperlink to thesearch result, a date on which the search result was created ormodified, keywords that appear in the search result, and other metadatathat describes the search result. The surrogate representations arepresented to a user in place of the search results, and the user mayselect at least a portion of a surrogate representation of a searchresult to access the search result corresponding to the surrogaterepresentation. In some implementations, portions of the surrogaterepresentations, such as the dates and the keywords, may not bepresented, but still may be considered when assigning scores.

The search interface assigns a score to each of the search results basedon visual characteristics of the surrogate representations (1510). Thescore assigned to a search result may depend on the presence of thequery in the surrogate representation of the search result. For example,the search result may be assigned a higher score when the query appearsin the surrogate representation of the search result than when the querydoes not appear in the surrogate representation. The score assigned to asearch result also may depend on a location of the query within thesurrogate representation of the search result. For example, a higherscore may be assigned to the search result when the query is included inthe title of the surrogate representation than when the query isincluded in the description of the surrogate representation.Alternatively or additionally, the score assigned to a search result maydepend on an amount of the query found in the surrogate representationof the search result. For example, a higher score may be assigned to thesearch result when the entire query is found in the surrogaterepresentation than when only a portion of the query is found in thesurrogate representation of the search result. The amount of the queryfound in the surrogate representation may be measured as a number ofterms within the query that are found in the surrogate representation,or as a percentage of the terms within the query that are found in thesurrogate representation.

The score assigned to a search result may depend on an amount of thesurrogate representation of the search result, or of a component of thesurrogate representation, reflecting terms from within the query. Forexample, a higher score may be assigned to the search result when thequery occupies a larger portion of surrogate representation than whenthe query occupies a smaller portion of the surrogate representation ofthe search result. The amount of the surrogate representation, or of thecomponent of the surrogate representation, that reflects query terms maybe measured as a percentage of the words in the surrogate representationor the component thereof that are query terms. The score assigned to asearch result also may depend on a distance between terms of the queryin the surrogate representation of the search result. For example, ahigher score may be assigned to the search result when the terms of thequery appear uninterrupted in the surrogate representation than when oneor more words are found between two of the terms of the query in thesurrogate representation of the search result. The score assigned to asearch result also may depend on an order of the terms of the query inthe surrogate representation of the search result. For example, a higherscore may be assigned to the search result when the order of the termsof the query is unchanged in the surrogate representation than when theorder of the terms of the query is changed in the surrogaterepresentation of the search result.

The score assigned to a search result also may depend on the dateincluded the surrogate representation of the search result. For example,the score of the search result may correspond directly to the age of thesearch result, which may be indicated by the corresponding date. In someimplementations, the score may be assigned to the search result based ona combination of the above-identified factors. In some implementations,the score identified for a search result based on the surrogaterepresentation of the search result may be combined with a scoreassigned to the search result by the one or more search engines.

In one implementation, the score assigned to a search result may dependon more than one of the above factors. In such an implementation, ascore may be assigned based on each of the factors, and weights may beused to combine the factor-specific scores into a single score for thesearch result. For example, a score of one may be assigned to the searchresult based on a first of the above described factors, and a score oftwo may be assigned based on a second of the above described factors.The first factor may have a weight of one, and the second factor mayhave a weight of two, so the score assigned to the search result may bethe sum of the products of each of the factor-specific scores and thecorresponding weight, which is five in the above example.

Weights also may be used when determining one of the factor specificscores. For example, a particular score may be assigned to a searchresult when the corresponding query appears in the surrogaterepresentation of the search result. In addition, weights may beassigned to parts of the surrogate representation such that a higherscore is assigned to the search result when the query is found inparticular parts of the surrogate representation. For example, a weightof three may be assigned to the title of the surrogate representation,and a weight of one may be assigned to the description of the surrogaterepresentation to indicate that the search result should be assigned ahigher score when the query appears in the title than when the queryappears in the description. The score assigned to the search resultbased on the presence of the query in the surrogate representation maybe the product of the particular score assigned to the search result asa result of the query appearing in the surrogate representation and theweight of the part of the surrogate representation in which the queryappears.

The search interface may order the search results based on the assignedscores (1515). Sorting the search results may include merging thereceived sets of search results into a single ordered list of searchresults. In one implementation, the search results may be ordered suchthat search results appear in order of decreasing score. The sortedsearch results may be presented to a user that submitted a query forwhich the search results have been identified. Alternatively, the searchresults may be processed further prior to presentation.

In some implementations, scores are assigned to the search results inone of the sets of search results such that the ordering of the searchresults within the set, which is based on scores assigned to the searchresults by the search engine from which the set of search results wasreceived, is unchanged. For example, when a first search result wasordered above a second search result by a search engine that returnedthe first and second search results, scores are assigned to the firstand second search results such that the first search result remainsordered above the second search result, even though visualcharacteristics of surrogate representations of the first and secondsearch results may indicate that the second search result should beordered above the first search result. In other words, the scoresassigned to the search results that are based on the surrogaterepresentations of the search results may be combined with the scoresassigned to the search results by the search engine, with the scoresassigned by the search engine being given a higher importance or weightin the overall score assigned to the search results. Assigning scores insuch a manner is advantageous because the search engine may consider awide array of information when scoring and ordering the search results,which results in the search engine being better suited to order thesearch results.

However, in implementations where the search results are received frommultiple search engines, assigning scores to the search results afterthe search results are received ensures that the search results arescored consistently, regardless of the search engine from which thesearch result was retrieved. Therefore, the search results are mergedbased on consistent scoring, which may reduce bias towards or away fromresults from a particular search engine.

Scoring the search results based on the visual characteristics of thesurrogate representations of the search results mimics user assessmentof the relevance of the search results. Therefore, search results that auser would assess as very relevant would be assigned a high score, andsearch results that a user would assess as not very relevant would beassigned a low score. As a result, the search results that the userwould assess as very relevant are presented first when the searchresults are ordered based on the assigned scores.

Referring to FIG. 16, the search tool user interface 600 displays searchresults 1605 a and 1605 b that are retrieved for a query that has beenentered in the text field 605 after the button 610 has been selected.More particularly, the search tool user interface 600 displays surrogaterepresentations of the search results 1605 a and 1605 b. The surrogaterepresentations 1605 a and 1605 b include titles 1610 a and 1610 b,descriptions 1615 a and 1615 b, addresses 1620 a and 1620 b, and dates1625 a and 1625 b, respectively.

The titles 1610 a and 1610 b are titles of the search results 1605 a and1605 b. The titles 1610 a and 1610 b may be hyperlinks that may beselected to access the search results 1605 a and 1605 b. Thedescriptions 1615 a and 1615 b are excerpts from, or short summaries of,the search results 1605 a and 1605 b. The descriptions 1615 a and 1615 bmay be specified to include one or more terms from the query. Theaddresses 1620 a and 1620 b identify locations from which the searchresults 1605 a and 1650 b may be accessed. The addresses 1620 a and 1620b also may be hyperlinks that may be selected to access the searchresults 1605 a and 1605 b. The dates 1625 a and 1625 b may identifydates on which the search results 1605 a and 1605 b were firstaccessible, or were last modified.

The search result 1605 a has been ordered before the search result 1605b based on scores that have been assigned to the search results 1605 aand 1605 b. The scores assigned to the search results 1605 a and 1650 bare based on visual characteristics of the surrogate representations ofthe search results 1605 a and 1605 b, as is described above with respectto the operation 1510 of the process 425 of FIG. 15. The search result1605 a may be ordered before the search result 1605 b because the queryentered in the text field 605 occupies a larger portion of the title1610 a than of the title 1610b. In addition, a higher score may be giveto the search result 1605 a because the entire query appearscontinuously in the description 1615 a, while the entire query does notappear continuously in the description 1615 b. Furthermore, the query isfound in the address 1620 a and is not found in the address 1620 b,which may indicate that the search result 1605 a should be given ahigher score than the search result 1605 b. The dates 1625 a and 1625 b,which indicate that the search result 1605 a is newer than the searchresult 1605 b, may indicate that the search result 1605 a should begiven a higher score than the search result 1605 b.

Referring to FIG. 17, a process 430 represents one implementation of theoperation 430 of FIG. 4, in which search results are filtered based onscores assigned to the search results. The process 430 may be executedby a search interface, such as the search interface 110 of FIG. 1, aspart of the process 400 of FIG. 4.

The search interface chooses two adjacent search results from a set ofsearch results to which scores have been assigned (1705). The scores maybe assigned to the search results according to the process 425 of FIG.15. Alternatively, the scores may have been assigned by a source fromwhich the search result was retrieved. Two search results are calledadjacent when no other search results have scores that are between thescores of the two search results. In implementations where high scoresrepresent high quality search results, the two adjacent search resultsthat are chosen may be the search results with the two highest assignedscores. In implementations where low scores represent high qualitysearch results, the two adjacent search results that are chosen may bethe search results with the two lowest assigned scores. The searchresults may be ordered to facilitate selection of the two adjacentsearch results.

The search interface determines a score differential between the twoadjacent search results (1710). The score differential is the differencebetween the scores assigned to the two adjacent search results. Thedifferential may be determined as an absolute score differential or as arelative score differential. For example, the score differential may bedetermined as a percentage of a maximum, minimum, or average score ofthe search results, as a percentage of the larger or the smaller of thescores of the two adjacent search results, as a percentage of adifference between the maximum and the minimum scores, or as apercentage of a difference between the scores of the two adjacent searchresults. The search interface determines whether the score differentialis too large (1715). In one implementation, the score differential maybe too large when the score differential exceeds a thresholddifferential. The threshold differential may be an absolute scoredifferential or a relative score differential, such as a percentage of amaximum, minimum, or average score of the search results, as apercentage of a difference between the maximum and the minimum scores, apercentage of a difference between the scores identified for the twoadjacent search results, or as a percentage of a standard deviation ofthe scores of the search results.

If the score differential is too large, then the search interfaceeliminates search results ordered below the lower ordered one of the twoadjacent search results (1720). For example, in implementations where alarge score is indicative of a high quality search result, searchresults with scores that are less than or equal to the smaller of thescores of the two adjacent search results may be eliminated. As anotherexample, in implementations where a small score is indicative of a highquality search result, search results with scores that are greater thanor equal to the larger of the scores of the two adjacent search resultsmay be eliminated. A large score differential between a first searchresult and a second search result indicates a large difference in thequalities of the first and second search results. More particularly, thelower ordered adjacent search result is of a significantly lower qualitythan the higher ordered adjacent search result. The lower quality searchresult may not be useful to a user for which the search results wereretrieved, as a result of being of the lower quality. Therefore, thatsearch result, and other search results with even lower qualities, maybe eliminated to prevent providing low quality search results to theuser.

If the score differential is not too large, then the search interfacedetermines whether more pairs of adjacent search results may be foundwithin the search results (1725). If so, then the search interfacechooses another pair of adjacent search results (1705), and the searchresults may be filtered based on the score differential between thechosen pair of adjacent search results (1710, 1715, 1720). In thismanner, pairs of adjacent search results are sequentially processed todetermine if search results should be eliminated based on scoredifferentials of the pairs of adjacent search results.

The search interface also may eliminate search results with scores lessthan or equal to a minimum allowable score (1730). Search results with ascore less than or equal to the minimum allowable score may be of a lowquality. The low quality search results may not be useful to a user forwhich the search results were retrieved, as a result of being of thelower quality. Therefore, those search results may be eliminated toprevent providing low quality search results to the user.

The described systems, methods, and techniques may be implemented indigital electronic circuitry, computer hardware, firmware, software, orin combinations of these elements. Apparatus embodying these techniquesmay include appropriate input and output devices, a computer processor,and a computer program product tangibly embodied in a machine-readablestorage device for execution by a programmable processor. A processembodying these techniques may be performed by a programmable processorexecuting a program of instructions to perform desired functions byoperating on input data and generating appropriate output. Thetechniques may be implemented in one or more computer programs that areexecutable on a programmable system including at least one programmableprocessor coupled to receive data and instructions from, and to transmitdata and instructions to, a data storage system, at least one inputdevice, and at least one output device. Each computer program may beimplemented in a high-level procedural or object-oriented programminglanguage, or in assembly or machine language if desired; and in anycase, the language may be a compiled or interpreted language. Suitableprocessors include, by way of example, both general and special purposemicroprocessors. Generally, a processor will receive instructions anddata from a read-only memory and/or a random access memory. Storagedevices suitable for tangibly embodying computer program instructionsand data include all forms of non-volatile memory, including by way ofexample semiconductor memory devices, such as Erasable ProgrammableRead-Only Memory (EPROM), Electrically Erasable Programmable Read-OnlyMemory (EEPROM), and flash memory devices; magnetic disks such asinternal hard disks and removable disks; magneto-optical disks; andCompact Disc Read-Only Memory (CD-ROM). Any of the foregoing may besupplemented by, or incorporated in, specially-designed ASICs(application-specific integrated circuits).

It will be understood that various modifications may be made withoutdeparting from the spirit and scope of the claims. For example,advantageous results still could be achieved if steps of the disclosedtechniques were performed in a different order and/or if components inthe disclosed systems were combined in a different manner and/orreplaced or supplemented by other components. Accordingly, otherimplementations are within the scope of the following claims.

What is claimed is:
 1. A computer-implemented method for resolving aquery, the method comprising: enabling display of an interface tosolicit multiple search terms in a single query; receiving, based on theinterface, multiple search terms in a single query; identifying multiplecategories applicable to a first portion of the multiple search terms;identifying multiple categories applicable to a second portion of themultiple search terms, the second portion of the multiple search termsbeing different than the first portion of the multiple search terms;determining that a category is among each of the multiple categoriesidentified as being applicable to the first portion of the multiplesearch terms and the multiple categories identified as being applicableto the second portion of the multiple search terms; identifying thedetermined category as being applicable to the received single query; inresponse to identifying the determined category as being applicable tothe single received query, performing a search process that uses thedetermined category in identifying search results responsive to thesingle received query; and storing, in electronic storage and using aprocessor, the identified search results.
 2. The method of claim 1wherein: identifying multiple categories applicable to the first portionof the multiple search terms comprises identifying multiple categoriesapplicable to a first portion of the multiple search terms that includesall of the multiple search terms; identifying multiple categoriesapplicable to the second portion of the multiple search terms comprisesidentifying multiple categories applicable to a second portion of themultiple search terms that includes less than all of the search terms.3. The method of claim 2 wherein identifying multiple categoriesapplicable to the second portion of the multiple search terms thatincludes less than all of the search terms comprises identifyingmultiple categories applicable to a second portion of the multiplesearch terms that includes only one of the multiple search terms.
 4. Themethod of claim 1 wherein: identifying multiple categories applicable tothe first portion of the multiple search terms comprises identifyingmultiple categories applicable to a first portion of the multiple searchterms that includes a first search term; identifying multiple categoriesapplicable to the second portion of the multiple search terms comprisesidentifying multiple categories applicable to a second portion of themultiple search terms that includes a second search term that isdifferent than the first search term.
 5. The method of claim 1 wherein:identifying multiple categories applicable to the first portion of themultiple search terms comprises identifying multiple categoriesapplicable to the first portion of the multiple search termsautomatically without user intervention; identifying multiple categoriesapplicable to the second portion of the multiple search terms comprisesidentifying multiple categories applicable to the second portion of themultiple search terms automatically without user intervention;determining that a category is among each of the multiple categoriesidentified as being applicable to the first portion of the multiplesearch terms and the multiple categories identified as being applicableto the second portion of the multiple search terms comprises determiningthat a category is among each of the multiple categories identified asbeing applicable to the first portion of the multiple search terms andthe multiple categories identified as being applicable to the secondportion of the multiple search terms automatically without userintervention; identifying the determined category as being applicable tothe single received query comprises identifying the determined categoryas being applicable to the single received query automatically withoutuser intervention; and performing the search process that uses thedetermined category in identifying search results responsive to thesingle received query comprises performing the search process that usesthe determined category in identifying search results responsive to thesingle received query automatically without user intervention.
 6. Themethod of claim 1 wherein performing the search process that uses thedetermined category in identifying search results responsive to thesingle received query comprises: accessing, from electronic storage, oneor more query terms associated with the determined category; configuringthe query to include the accessed one or more query terms associatedwith the determined category, the configured query being different thanthe query; and performing a search process using the configured query.7. The method of claim 6 wherein performing the search process using theconfigured query: submitting the configured query to a search engine;and receiving, from the search engine, search results corresponding tothe configured query.
 8. The method of claim 6 wherein configuring thequery to include the accessed one or more query terms associated withthe determined category comprises formatting the query into a canonicalform of the query for the determined category.
 9. The method of claim 6wherein configuring the query to include the accessed one or more queryterms associated with the determined category comprises adding theaccessed one or more query terms associated with the determined categoryto the query, the accessed one or more query terms associated with thedetermined category being one or more keywords associated with thedetermined category in a query ontology.
 10. The method of claim 1wherein: determining that a category is among each of the multiplecategories identified as being applicable to the first portion of themultiple search terms and the multiple categories identified as beingapplicable to the second portion of the multiple search terms comprisesdetermining that a single category is among each of the multiplecategories identified as being applicable to the first portion of themultiple search terms and the multiple categories identified as beingapplicable to the second portion of the multiple search terms; andidentifying the determined category as being applicable to the singlereceived query comprises identifying the single category as beingapplicable to the single received query.
 11. The method of claim 10wherein identifying the single category as being applicable to thesingle received query comprises identifying the single category as theonly category among the multiple categories identified as beingapplicable to the first portion of the multiple search terms and themultiple categories identified as being applicable to the second portionof the multiple search terms as being applicable to the single receivedquery.
 12. A machine-accessible medium that when accessed, results in amachine performing operations for resolving a query, comprising:enabling display of an interface to solicit multiple search terms in asingle query; receiving, based on the interface, multiple search termsin a single query; identifying multiple categories applicable to a firstportion of the multiple search terms; identifying multiple categoriesapplicable to a second portion of the multiple search terms, the secondportion of the multiple search terms being different than the firstportion of the multiple search terms; determining that a category isamong each of the multiple categories identified as being applicable tothe first portion of the multiple search terms and the multiplecategories identified as being applicable to the second portion of themultiple search terms; identifying the determined category as beingapplicable to the received single query; in response to identifying thedetermined category as being applicable to the single received query,performing a search process that uses the determined category inidentifying search results responsive to the single received query; andstoring, in electronic storage and using a processor, the identifiedsearch results.
 13. The machine-accessible medium of claim 12 wherein:identifying multiple categories applicable to the first portion of themultiple search terms comprises identifying multiple categoriesapplicable to a first portion of the multiple search terms that includesall of the multiple search terms; identifying multiple categoriesapplicable to the second portion of the multiple search terms comprisesidentifying multiple categories applicable to a second portion of themultiple search terms that includes less than all of the search terms.14. The machine-accessible medium of claim 13 wherein identifyingmultiple categories applicable to the second portion of the multiplesearch terms that includes less than all of the search terms comprisesidentifying multiple categories applicable to a second portion of themultiple search terms that includes only one of the multiple searchterms.
 15. The machine-accessible medium of claim 12 wherein:identifying multiple categories applicable to the first portion of themultiple search terms comprises identifying multiple categoriesapplicable to a first portion of the multiple search terms that includesa first search term; identifying multiple categories applicable to thesecond portion of the multiple search terms comprises identifyingmultiple categories applicable to a second portion of the multiplesearch terms that includes a second search term that is different thanthe first search term.
 16. The machine-accessible medium of claim 12wherein: identifying multiple categories applicable to the first portionof the multiple search terms comprises identifying multiple categoriesapplicable to the first portion of the multiple search termsautomatically without user intervention; identifying multiple categoriesapplicable to the second portion of the multiple search terms comprisesidentifying multiple categories applicable to the second portion of themultiple search terms automatically without user intervention;determining that a category is among each of the multiple categoriesidentified as being applicable to the first portion of the multiplesearch terms and the multiple categories identified as being applicableto the second portion of the multiple search terms comprises determiningthat a category is among each of the multiple categories identified asbeing applicable to the first portion of the multiple search terms andthe multiple categories identified as being applicable to the secondportion of the multiple search terms automatically without userintervention; identifying the determined category as being applicable tothe single received query comprises identifying the determined categoryas being applicable to the single received query automatically withoutuser intervention; and performing the search process that uses thedetermined category in identifying search results responsive to thesingle received query comprises performing the search process that usesthe determined category in identifying search results responsive to thesingle received query automatically without user intervention.
 17. Themachine-accessible medium of claim 12 wherein performing the searchprocess that uses the determined category in identifying search resultsresponsive to the single received query comprises: accessing, fromelectronic storage, one or more query terms associated with thedetermined category; configuring the query to include the accessed oneor more query terms associated with the determined category, theconfigured query being different than the query; and performing a searchprocess using the configured query.
 18. The machine-accessible medium ofclaim 12 wherein: determining that a category is among each of themultiple categories identified as being applicable to the first portionof the multiple search terms and the multiple categories identified asbeing applicable to the second portion of the multiple search termscomprises determining that a single category is among each of themultiple categories identified as being applicable to the first portionof the multiple search terms and the multiple categories identified asbeing applicable to the second portion of the multiple search terms; andidentifying the determined category as being applicable to the singlereceived query comprises identifying the single category as beingapplicable to the single received query.
 19. The machine-accessiblemedium of claim 18 wherein identifying the single category as beingapplicable to the single received query comprises identifying the singlecategory as the only category among the multiple categories identifiedas being applicable to the first portion of the multiple search termsand the multiple categories identified as being applicable to the secondportion of the multiple search terms as being applicable to the singlereceived query.
 20. A computer system comprising: at least oneprocessor; and at least one machine-readable storage device encoded withmachine readable instructions that, when executed by the at least oneprocessor, operate to cause the at least one processor to performoperations comprising: enabling display of an interface to solicitmultiple search terms in a single query; receiving, based on theinterface, multiple search terms in a single query; identifying multiplecategories applicable to a first portion of the multiple search terms;identifying multiple categories applicable to a second portion of themultiple search terms, the second portion of the multiple search termsbeing different than the first portion of the multiple search terms;determining that a category is among each of the multiple categoriesidentified as being applicable to the first portion of the multiplesearch terms and the multiple categories identified as being applicableto the second portion of the multiple search terms; identifying thedetermined category as being applicable to the received single query; inresponse to identifying the determined category as being applicable tothe single received query, performing a search process that uses thedetermined category in identifying search results responsive to thesingle received query; and storing, in electronic storage and using aprocessor, the identified search results.